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Integrated single-nucleotide and structural variation signatures of DNA-repair deficient human cancers

View ORCID ProfileTyler Funnell, Allen Zhang, Yu-Jia Shiah, Diljot Grewal, Robert Lesurf, Steven McKinney, Ali Bashashati, Yi Kan Wang, Paul C. Boutros, Sohrab P. Shah
doi: https://doi.org/10.1101/267500
Tyler Funnell
1Department of Molecular Oncology, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, V5Z 1L3, Canada
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  • ORCID record for Tyler Funnell
Allen Zhang
1Department of Molecular Oncology, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, V5Z 1L3, Canada
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Yu-Jia Shiah
2Informatics & Biocomputing, Ontario Institute for Cancer Research, Toronto, Canada
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Diljot Grewal
1Department of Molecular Oncology, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, V5Z 1L3, Canada
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Robert Lesurf
2Informatics & Biocomputing, Ontario Institute for Cancer Research, Toronto, Canada
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Steven McKinney
1Department of Molecular Oncology, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, V5Z 1L3, Canada
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Ali Bashashati
1Department of Molecular Oncology, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, V5Z 1L3, Canada
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Yi Kan Wang
1Department of Molecular Oncology, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, V5Z 1L3, Canada
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Paul C. Boutros
2Informatics & Biocomputing, Ontario Institute for Cancer Research, Toronto, Canada
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Sohrab P. Shah
1Department of Molecular Oncology, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, V5Z 1L3, Canada
3Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, V6T 2B5, Canada
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Abstract

Mutation signatures in cancer genomes reflect endogenous and exogenous mutational processes, offering insights into tumour etiology, features for prognostic and biologic stratification and vulnerabilities to be exploited therapeutically. We present a novel machine learning formalism for improved signature inference, based on multi-modal correlated topic models (MMCTM) which can at once infer signatures from both single nucleotide and structural variation counts derived from cancer genome sequencing data. We exemplify the utility of our approach on two hormone driven, DNA repair deficient cancers: breast and ovary (n=755 cases total). Our results illuminate a new age-associated structural variation signature in breast cancer, and an independently identified substructure within homologous recombination deficient (HRD) tumours in breast and ovarian cancer. Together, our study emphasizes the importance of integrating multiple mutation modes for signature discovery and patient stratification, with biological and clinical implications for DNA repair deficient cancers.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 18, 2018.
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Integrated single-nucleotide and structural variation signatures of DNA-repair deficient human cancers
Tyler Funnell, Allen Zhang, Yu-Jia Shiah, Diljot Grewal, Robert Lesurf, Steven McKinney, Ali Bashashati, Yi Kan Wang, Paul C. Boutros, Sohrab P. Shah
bioRxiv 267500; doi: https://doi.org/10.1101/267500
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Integrated single-nucleotide and structural variation signatures of DNA-repair deficient human cancers
Tyler Funnell, Allen Zhang, Yu-Jia Shiah, Diljot Grewal, Robert Lesurf, Steven McKinney, Ali Bashashati, Yi Kan Wang, Paul C. Boutros, Sohrab P. Shah
bioRxiv 267500; doi: https://doi.org/10.1101/267500

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